{"id":"W4382468067","doi":"10.1007/s10705-023-10294-w","title":"Canola productivity and carbon footprint under different cropping systems in eastern Canada","year":2023,"lang":"en","type":"article","venue":"Nutrient Cycling in Agroecosystems","topic":"Soil Carbon and Nitrogen Dynamics","field":"Agricultural and Biological Sciences","cited_by":14,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Environment and Climate Change Canada; McGill University; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Alberta Canola Producers Commission; Dalhousie University; Canola Council of Canada; Saskatchewan Canola Development Commission; McGill University","keywords":"Canola; Monoculture; Agronomy; Cropping system; Cropping; Brassica; Crop rotation; Crop yield; Carbon footprint; Productivity; Yield (engineering); Agriculture; Environmental science; Crop; Biology; Greenhouse gas","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003013044,0.0003296265,0.0001957004,0.0009579929,0.001611027,0.0008832988,0.0006157189,0.0001339146,0.0009953367],"category_scores_gemma":[0.0003625121,0.000146588,0.0002442691,0.001875031,0.0004430193,0.0002543365,0.0003367522,0.0002363228,0.0001089751],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.03117469,"about_ca_system_score_gemma":0.01420629,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9919634,"about_ca_topic_score_gemma":0.9982077,"domain_scores_codex":[0.9997271,0.00001393185,0.000008003251,0.00005543624,0.00007797063,0.0001176617],"domain_scores_gemma":[0.999388,0.0000297585,0.00006023721,0.00002286085,0.0003604395,0.0001386755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008827696,0.0002865311,0.9303566,0.0001179718,0.0002560903,0.0005611097,0.001505301,0.002475581,0.02967206,0.0005172966,0.001480289,0.03188841],"study_design_scores_gemma":[0.000008556358,0.0000416451,0.995631,0.000007685069,0.00002837883,0.00003477972,0.00131701,0.0006589391,0.0009073365,0.00002183085,0.001332493,0.0000104522],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971656,0.0001689349,0.00007354207,0.00003977773,0.000001945202,0.00002154367,0.00101362,0.00001016044,0.001504967],"genre_scores_gemma":[0.9968147,0.0001801787,0.0003083763,0.00002409569,7.181949e-7,0.00001172069,0.0009494152,0.000003480907,0.001707387],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03117469,"threshold_uncertainty_score":0.2261893,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02085929615426011,"score_gpt":0.2140344771051413,"score_spread":0.1931751809508812,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}